Articles | Volume 19, issue 18
https://doi.org/10.5194/gmd-19-9177-2026
https://doi.org/10.5194/gmd-19-9177-2026
Development and technical paper
 | 
28 Sep 2026
Development and technical paper |  | 28 Sep 2026

Effectively assimilate satellite land surface temperature into offline land surface models within ensemble-based assimilation frameworks

Yunhao Fu, Yongjun Zheng, and Jingjia Luo

Data sets

Results from 'Effectively Assimilate Satellite Land Surface Temperature into Offline Land Surface Models within Ensemble-based Assimilation Frameworks' Yunhao Fu and Yongjun Zheng https://doi.org/10.5281/zenodo.22721603

Near surface meteorological variables from 1979 to present derived from bias-corrected reanalysis Copernicus Climate Change Service, Climate Data Store https://doi.org/10.24381/cds.20d54e34

Land Surface Temperature from MODIS (Moderate resolution Infra-red Spectroradiometer) on Terra, level 3 collated (L3C) global product (2000–2018) ESA Land Surface Temperature Climate Change Initiative https://doi.org/10.5285/58a01734f841466daa1837353aee5ff8

ERA5-Land hourly data from 1950 to present, Copernicus Climate Change Service Copernicus Climate Change Service, Climate Data Store https://doi.org/10.24381/cds.e2161bac

MERRA-2 2d,1-Hourly,Time-Averaged,SingleLevel,Assimilation,Land Surface Diagnostics V5.12.4 NASA Global Modeling and Assimilation Office (GMAO) https://doi.org/10.5067/RKPHT8KC1Y1T

GLDAS Noah Land Surface Model L4 3-hourly 0.25×0.25 degree V2.1 NASA Global Land Data Assimilation System https://doi.org/10.5067/E7TYRXPJKWOQ

Results from “Effectively Assimilate Satel- lite Land Surface Temperature into Offline Land Surface Models within Ensemble-based Assimilation Frameworks” Y. Fu and Y. Zheng https://doi.org/10.5281/zenodo.17284395

Model code and software

Source code of the Common Land Model (CoLM), MPI version 2010 The Common Land Model (CoLM) https://doi.org/10.5281/zenodo.18649912

LETKF-CoLM for Effectively Assimilate Satellite Land Surface Temperature into Offline Land Surface Models within Ensemble-based Assimilation Frameworks Yunhao Fu and Yongjun Zheng https://doi.org/10.5281/zenodo.18649772

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Short summary
It is challenging to assimilate land surface temperature (LST) owing to its fast temporally varying nature. This study proposes a scheme by jointly updating the soil temperature and soil moisture. Results show marginal enhancement in LST, yet soil temperature bias over Northeast Asia (NA) drops sharply. Snow temperature and snow depth over NA, and soil moisture in the humid tropics also improve significantly. These consistent improvements demonstrate the effectiveness of the proposed scheme.
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